Reflecting on this example and your x-risk questions, this highlights the fact that in the beta(0.1,0.1) case, we’re either very likely fine or really screwed, whereas in the beta(20,20) case, it’s similar to a fair coin toss. So it feels easier to me to get motivated to work on mitigating the second one. I don’t think that says much about which is higher priority to work on though because reducing the risk in the first case could be super valuable. The value of information narrowing uncertainty in the first case seems much higher though.
I share the intuition that the second case would be easier to get people motivated for, as it represents more of a confirmed loss.
However, as your example shows actually the first case could lead to an ‘in it together’ effect on co-ordination. Assuming the information is taken seriously. Which is hard as, in advance, this kind of situation could encourage a ‘roll the dice’ mentality.
Reflecting on this example and your x-risk questions, this highlights the fact that in the beta(0.1,0.1) case, we’re either very likely fine or really screwed, whereas in the beta(20,20) case, it’s similar to a fair coin toss. So it feels easier to me to get motivated to work on mitigating the second one. I don’t think that says much about which is higher priority to work on though because reducing the risk in the first case could be super valuable. The value of information narrowing uncertainty in the first case seems much higher though.
Nice example, I see where you’re going with that.
I share the intuition that the second case would be easier to get people motivated for, as it represents more of a confirmed loss.
However, as your example shows actually the first case could lead to an ‘in it together’ effect on co-ordination. Assuming the information is taken seriously. Which is hard as, in advance, this kind of situation could encourage a ‘roll the dice’ mentality.